Murderbots, mass layoffs, and media takeovers — all in one news cycle. Anthropic told the Pentagon "we will not accede." Block cut half its workforce overnight. And the Paramount-Warner Brothers deal raises real questions about who's running the media now.

Also, thanks to Nicolás Maduro's fashion sense, Dan's 13-year-old is being called Lil Tator at school and honestly? The kids are all right.

Happy FAFO Friday!

Of all the industries AI will transform, Kira Radinsky believes chemistry and biology will change the most.

Kira is the co-founder and CTO of Diagnostic Robotics, which uses AI to automate the administrative work that's crushing healthcare teams — so clinicians can actually focus on patients. She's also the co-founder of Mana.bio, where they're accelerating drug discovery by orders of magnitude.

She'll tell you she's terrible in the lab. Not because she isn't brilliant, but because she can't pipette without killing the cells. So she’s thrilled that thanks to her skills in data and AI she was able to realize her childhood dream of being a scientist:

But this episode is about more than healthcare. It's about how to build systems that get smarter over time — feedback loops, causal inference, incentivizing algorithms to take risks, and knowing when to optimize for ROI instead of accuracy. Lessons that apply whether you're building in biotech or not.

We cover:

• How growing up Jewish in Soviet Ukraine — and fleeing to Israel just before the Gulf War — shaped Kira's obsession with predicting the future
• How she built a system that successfully predicted real-world events, including Cuba's first cholera outbreak in Cuba in 130 years
• How Mana.bio is using AI to build "rocketships" that deliver drugs to the right cells — and how they've done in three months what used to take 20 years
• Why predictions are only valuable if there's something you can do about them — and why that makes healthcare an ideal field for AI
• How to incentivize algorithms to make bolder predictions (it's easy to predict there won't be an earthquake today; it's much harder to say there will be)
• Why causal inference is the most underrated tool in machine learning right now
• How healthcare AI can perpetuate racial bias — and what builders need to do differently

Note: this interview originally aired in October 2024.

Chapters:

• (01:44) - Why predictions are so important to Kira: lessons from fleeing Soviet-era Kyiv
• (05:10) - Building a prediction engine from 150 years of news
• (08:35) - How Kira predicted the Cuba cholera outbreak
• (09:50) - Returning to biology by way of data
• (12:50) - Predicting healthcare outcomes by finding your patient's twin
• (17:53) - The racial bias hiding in healthcare AI
• (19:15) - Building Mana.bio and accelerating drug discovery
• (24:33) - "In three months, what did what used to take 20 years"
• (31:44) - Builder tips: ROI, causal inference, and teaching algorithms to explore
• (35:07) - Planning: Where generative AI needs improve

• Kira Radinsky on LinkedIn
• Diagnostic Robotics
• Mana.bio

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Music by Jonathan Zalben

You probably know by now that AI is the definition of mediocre. As in: it’s the average of everything it’s been trained on. So how do you get beyond average? How do you build a moat?

It certainly doesn’t seem to be via the models. While there are models of the month (hey, Opus 4.6, my new friend!), they seem to be pretty swappable.

So, the model ain’t it. But proprietary data (e.g. an AI that knows you really well), yes! Or doing something really hard in the real world (think: Waymo self-driving cars). Maybe via trust and safety (Anthropic is certainly making a play here). Or... how about via amazing design and good taste.

Remember when ChatGPT first came out and everyone derided “AI wrappers”… well, maybe a wrapper isn’t so bad, assuming you can differentiate on one or more of the above.

Luke Des Cotes is the CEO of MetaLab, the agency famous for designing interfaces, including early versions of Slack and Coinbase, so don’t be shocked when you hear him say that great design can be your moat.

MetaLab is working with a host of AI companies (another shocker), including Windsurf (AI + code), Suno (AI + music), Pika (AI + video), and more…, which is why Luke's take on AI surprised me. He's not rah rah. He's pretty judicious actually. Luke has questions about AI's costs and appropriateness for lots of use cases like those involving kids, but mostly he objects to its mediocrity.

On this episode we discuss what it takes to go beyond.

We also get into:

• Why vibe-coded software isn't changing the world anytime soon
• Why Shopify acquired a design agency right after telling employees to justify their existence against AI
• How MetaLab designers are using AI to prototype in hours instead of weeks
• The talent market for zero-to-one designers — and why they're harder to find than ever
• Landlines, brick phones, and how parents are fighting back against always-on kids

Chapters

• (01:10) - "It's a race to the mean"
• (03:10) - "How do you create emotional resonance?"
• (05:33) - AI companies are burning money
• (08:44) - Speed to good enough
• (13:51) - Is the chat here to stay or a temporary fad?
• (17:43) - It’s hard to find great 0 to 1 design talent
• (22:28) - Seemingly conscious AI
• (25:05) - Kids, landlines, and fighting always-on culture
• (27:21) - Sounds like science fiction, but is here now…

Links & Resources

• Luke Des Cotes on LinkedIn
• MetaLab

Support Future Around & Find Out

• Get the free newsletter
• And consider becoming a paid subscriber and help future proof this thing!

Sponsor the show?

• Are you looking to reach an audience of senior technologists and decision-makers? Email me: dan@modernproductminds.com